Optimal two-stage filtering of elastograms

In ultrasound elastography, tissue axial strains are obtained through the differentiation of measured axial displacements. However, during the measurement process, the displacement signals are often contaminated with de-correlation noise caused by changes in the speckle pattern in the tissue. Thus, the application of the gradient operator on the displacement signals results in the presence of amplified noise in the axial strains, which severely obscures the useful information. The use of an effective denoising scheme is therefore imperative. In this paper, a method based on a two-stage consecutive filtering approach is proposed for the accurate estimation of axial strains. The presented method considers a cascaded system of a frequency filter and a time window, which are both designed such that the overall system operates optimally as a minimum variance estimator. Experimentation on simulated signals shows that the two-stage scheme employed in this study has good potential as a denoising method for ultrasound elastograms

Filtering in Rotated Time-Frequency Domains With Unknown Noise Statistics

The concept of rotation in the joint time-frequency plane can be exploited in order to generalize classical Fourier-based operations. It is known that filtering in rotated time-frequency domains can lead to significant performance advantages for certain types of signals as compared to conventional linear time invariant systems. In this correspondence, we revisit the design problem of such a scheme and derive a formulation that does not require knowledge of the statistics of the corrupting noise. Simulations have been used to confirm the validity of the proposed solution. © 2006 IEEE